AMD’s RDNA 4 Modular SoC & What’s Next: UDNA (RDNA 5) Eyes, Chips, and Strategy

AMD’s RDNA 4 architecture has quietly begun redefining what “flexible GPU design” means in 2025. At Hot Chips and in recent disclosures, the company revealed that RDNA 4 uses a modular System-on-Chip (SoC) architecture that allows scaling between different GPU variants with fewer bespoke designs. Meanwhile, rumors of the UDNA (or RDNA 5) generation suggest a significant leap in compute units, memory interface width, and ray tracing / AI enhancements.

In this analysis, we’ll break down the current state of RDNA 4’s modular design, what new features AMD has introduced, the prospects and leaks around UDNA, and how all of this stacks up against NVIDIA’s Rubin / Blackwell evolution. If you want to understand where the GPU arms race is headed, this is where it’s happening.

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RDNA 4: Modular Architecture Unpacked

What AMD Has Revealed

At Hot Chips 2025, AMD disclosed key details about RDNA 4’s design, emphasizing its modular nature. The takeaway:

• AMD is using a base SoC design comprising shader engines, multiple memory controllers, L3 cache, and display / power management subsystems as modular building blocks.

• For smaller or lower-end GPU variants, the SoC can be “cut down” by disabling or omitting certain shader engines or memory controllers, without needing a completely new layout/design.

• New memory & bandwidth compression techniques are being introduced to optimize performance per mm² and per watt, especially in mid-range SKUs.

Benefits & Implications

This modular SoC approach has several technical and business advantages:

1. Faster Time-to-Market / Validation Efficiency
   With fewer fundamentally different layouts to validate (PCB, thermal, power, yields), AMD can roll out more SKUs more quickly with predictable behaviour.

2. Reduced Development Cost
   Designing each GPU variant from scratch is costly. By sharing parts of the design (shader engines, memory controllers, display I/O), AMD can save engineering resources, die mask costs, and validation time.

3. Better Yield Management
   If certain parts of a die have lower yield (e.g. one shader engine), AMD can disable those sections and sell at a lower bin rather than scrapping or severely discounting imperfect dies.

4. Power & Thermal Scaling
   Because modular sections can be disabled for lower power variants, AMD has more control over TDP scaling. This helps both in mid-range cards (lower power draw) and premium ones (pushing performance) without needing completely different chip sizes.

Technical Details

Some of the specific features AMD has introduced or refined under RDNA 4:

• Shader Engines (SEs) that can be added or removed; memory controllers similarly modular.

• An updated Infinity Fabric / on-die interconnect that supports more flexible data flows between shader engines, memory controllers, L3 cache, and display / power blocks. This is crucial because as you disable or vary modules, latency, coherence, and interconnect bandwidth become bottlenecks.

• Enhanced compression / bandwidth-efficiency improvements (memory bandwidth reduction, better memory controller logic, perhaps more advanced caching or data-path optimisations) to allow mid-range SKUs to deliver good performance without excessive power or cost.

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UDNA (or RDNA 5) Rumors: What’s Leaking

If RDNA 4 sets up the modular SoC foundation, UDNA appears to be positioned to extend that foundation significantly. Leaks & reports suggest:

• Compute Units (CUs): UDNA flagship variants could have up to 96 CUs, which is about a ~50% increase over the largest RDNA 4 chips.

• Wider Memory Interface: Reports suggest a move to a 384-bit memory bus on flagship variants, potentially combined with faster GDDR7 or even more advanced memory tech.

• Possible Chiplet or Multi-SoC Designs: Some speculation that AMD may use multiple SoCs (or chiplets) in UDNA to build very high-end GPUs (e.g., “AT0” style chips) by stacking or aggregating mid-range SoC designs. This would echo how CPU chiplets have been used.

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Comparison vs NVIDIA: Rubin / Blackwell

Understanding AMD’s strategy in isolation is useful, but it only tells half the story. NVIDIA’s Rubin (successor to Blackwell) is in its way setting the bar:

• Rubin is expected around 2026, with HBM4 or similar high bandwidth memory, significant improvements in AI and inference throughput.

• Blackwell Ultra (current generation) already shows strong inference performance, and Rubin needs to further improve in tensor / AI workloads.

What this means: AMD’s UDNA will need to match or beat NVIDIA in both gaming (raster, ray tracing) and AI/tensor workloads. The modular SoC design gives AMD flexibility, but achieving high clock speeds, efficient ray tracing, and excellent driver & software support will be necessary to close the gap.

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Potential Upsides & Risks for AMD

Upsides

• SKU Diversity: With modular SoCs, AMD can more easily populate the market with mid-range, entry, and high-end variants without creating whole new chip designs.

• Cost Efficiency: Die reuse, better yield, shared components reduce costs — theoretically allowing more aggressive pricing or higher margins.

• Scalability for AI & Future Workloads: As AI becomes more important (inference, upscaling, etc.), having flexible hardware that can adapt (via AI accelerators, etc.) is valuable.

Risks

• Power Efficiency: as CU count increases, and memory buses widen, power draw and heat become big challenges. Unless RDNA 5/UDNA optimizes efficiency aggressively, gains may be tarnished by high consumption.

• Driver and Software Maturity: Modular design complexity increases firmware/driver challenges. Ensuring that disabled shader engines behave cleanly, memory controllers handle variability, and performance is smooth across variants is non-trivial.

• Fabrication Lead Time & Yield: Larger dies or more complex chiplets risk yield problems. Also adopting new memory tech (e.g. GDDR7) or interconnects may be delayed or more expensive.

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What This Means for Gamers and the Market

For consumers and enthusiasts, here are likely outcomes:

• More Mid-Range / Value GPUs: Because of modularity, AMD can produce more efficient mid-range cards with good performance, possibly with better price-to-performance ratios.

• Flagship Models That Are More Ambitious: UDNA variants could push flagships harder, giving steeper upgrades in ray tracing, AI upscaling, etc.

• Faster Turnover of Models: Modular SoC design may let AMD refresh its lineup more often, tweaking variant specs without full new chips.

• Pressure on Pricing: If AMD leverages cost savings, retailers might see more aggressive MSRP or volume discounts, especially in mid-segment.

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What to Watch Next

Here are the key milestones and signals to monitor:

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Conclusion

AMD’s adoption of a modular SoC architecture in RDNA 4 represents an important shift—one that may redefine how GPU variants are built, how yields are managed, and how performance per dollar scales. With UDNA (or RDNA 5) rumored to bring ~50% more compute units, wider memory interfaces, and possibly multi-SoC designs, the stakes are high.

If AMD executes well, the result could be a GPU lineup that is more agile, more efficient, and more competitive across both gaming and AI workloads. But execution will matter: efficiency, driver maturity, cooling, yield, and pricing are the chinks in the armour.

For now, RDNA 4 sets the base; UDNA will be the test of whether the modular GPU future AMD envisions delivers not just in theory, but in the hands of gamers and creators.